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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- govreport-summarization |
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metrics: |
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- rouge |
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model-index: |
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- name: flan-t5-gov-report-sum |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: govreport-summarization |
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type: govreport-summarization |
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config: document |
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split: test |
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args: document |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 5.8729 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# flan-t5-gov-report-sum |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the govreport-summarization dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2385 |
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- Rouge1: 5.8729 |
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- Rouge2: 3.0763 |
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- Rougel: 5.1016 |
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- Rougelsum: 5.646 |
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- Gen Len: 19.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 2.5801 | 1.0 | 2190 | 2.3211 | 5.6226 | 2.9142 | 4.9535 | 5.417 | 19.0 | |
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| 2.5125 | 2.0 | 4380 | 2.2748 | 5.7982 | 3.0365 | 5.0726 | 5.5837 | 19.0 | |
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| 2.453 | 3.0 | 6570 | 2.2545 | 5.8744 | 3.0997 | 5.1196 | 5.6524 | 19.0 | |
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| 2.436 | 4.0 | 8760 | 2.2430 | 5.8669 | 3.0525 | 5.0849 | 5.631 | 19.0 | |
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| 2.4144 | 5.0 | 10950 | 2.2385 | 5.8729 | 3.0763 | 5.1016 | 5.646 | 19.0 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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